National Science Library of Georgia

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Statistical models : theory and practice / David A. Freedman.

By: Material type: TextTextPublisher: Cambridge : Cambridge University Press, 2009Edition: Second editionDescription: 1 online resource (xiv, 442 pages) : digital, PDF file(s)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780511815867 (ebook)
Subject(s): Additional physical formats: Print version: : No titleDDC classification:
  • 519.5 22
LOC classification:
  • QA279 .F74 2009
Online resources:
Contents:
Observed studies and experiments -- The regression line -- Matrix algebra -- Multiple regression -- Multiple regression: Special topics -- Path models -- Maximum likelihood -- The bootstrap -- Simultaneous equations -- Issues in statistical modeling.
Summary: This lively and engaging book explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The discussion in the book is organized around published studies, as are many of the exercises. Relevant journal articles are reprinted at the back of the book. Freedman makes a thorough appraisal of the statistical methods in these papers and in a variety of other examples. He illustrates the principles of modelling, and the pitfalls. The discussion shows you how to think about the critical issues - including the connection (or lack of it) between the statistical models and the real phenomena. The book is written for advanced undergraduates and beginning graduate students in statistics, as well as students and professionals in the social and health sciences.
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Title from publisher's bibliographic system (viewed on 05 Oct 2015).

Observed studies and experiments -- The regression line -- Matrix algebra -- Multiple regression -- Multiple regression: Special topics -- Path models -- Maximum likelihood -- The bootstrap -- Simultaneous equations -- Issues in statistical modeling.

This lively and engaging book explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The discussion in the book is organized around published studies, as are many of the exercises. Relevant journal articles are reprinted at the back of the book. Freedman makes a thorough appraisal of the statistical methods in these papers and in a variety of other examples. He illustrates the principles of modelling, and the pitfalls. The discussion shows you how to think about the critical issues - including the connection (or lack of it) between the statistical models and the real phenomena. The book is written for advanced undergraduates and beginning graduate students in statistics, as well as students and professionals in the social and health sciences.

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